Memory Affinity: Balancing Performance, Power, Thermal and Fairness for Multi-core Systems

Experimental results demonstrate the memory affinity aware scheduling algorithms well adapt to system loading to maximize power saving and avoid memory hotspot at the same time while sustaining the system bandwidth demand and preserving fairness among threads.

Abstract

Main memory is expected to grow significantly in both speed and capacity for it is a major shared resource among cores in a multi-core system, which will lead to increasing power consumption. Therefore, it is critical to address the power issue without seriously decreasing performance in the memory subsystem. In this paper, we firstly propose memory affinity which retains the active and low power memory ranks as long as possible to avoid frequently switching between active and low power status, and then present a memory affinity aware scheduling (MAS) to balance performance, power, thermal and fairness for multi-core systems. Experimental results demonstrate our memory affinity aware scheduling algorithms well adapt to system loading to maximize power saving and avoid memory hotspot at the same time while sustaining the system bandwidth demand and preserving fairness among threads.